Authors:
Hirotaka Goto
1
;
Asuka Ohta
1
;
Tomofumi Matsuzawa
1
;
Munehiro Takimoto
1
;
Yasushi Kambayashi
2
and
Masayuki Takeda
1
Affiliations:
1
Tokyo University of Science, Japan
;
2
Nippon Institute of Technology, Japan
Keyword(s):
Ant Colony Optimization, Route Guidance System, Swarm Intelligence, Disaster Simulation, Seismic Disaster.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Bioinformatics
;
Biomedical Engineering
;
Distributed Problem Solving
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Methodologies and Technologies
;
Operational Research
;
Simulation
Abstract:
This paper reports the results of applying our approach discovering safe evacuation routes to practical situations.
Our approach is based on the ant colony optimization (ACO) and it is practical in the light of a real case
with a tsunami. ACO have been often employed for finding evacuation routes in traditional approaches, which
only take advantage of ants behavior more frequently following traces of other ants’ through pheromone communications.
We assume that there are a lot of danger zones in the damaged area. For example Rikuzentakata
is a city that extensively damaged in the 2011 Great East Japan Earthquake. In such a case, the traditional
approaches may present some unsafe routes through the danger zones. We have proposed an ACO based
approach that calculates evacuation routes avoiding danger zones. In our approach, evacuees can deposit deodorant
pheromone around danger zones, which makes normal pheromone ineffective, so that our approach
gives routes not passing through the dan
ger zones. We have implemented our approach as a simulator, conducting
experiments in the same situation as the Rikuzentakata case. Through the results of the experiments,
we show that our approach decreases the number of people suffering from collapsed and burning buildings.
(More)